Price: $24.99
(as of Dec 23,2024 14:37:07 UTC – Details)

ASIN ‏ : ‎ B0CMB9TB7Y
Publisher ‏ : ‎ Independently published (October 30, 2023)
Language ‏ : ‎ English
Paperback ‏ : ‎ 251 pages
ISBN-13 ‏ : ‎ 979-8864900970
Item Weight ‏ : ‎ 12.5 ounces
Dimensions ‏ : ‎ 6 x 0.57 x 9 inches

Are you preparing for a data engineering interview and feeling overwhelmed by the technical questions? Don’t worry, we’ve got you covered! In this post, we’ll provide you with a comprehensive guide to help you ace the data engineering interview. We’ll cover common questions and answers for Python, SQL, data modeling, and more. Let’s dive in!

1. Python:
Q: What is the difference between lists and tuples in Python?
A: Lists are mutable, meaning they can be modified after creation, while tuples are immutable, meaning they cannot be changed. Tuples are also faster than lists because they are fixed in size.

Q: Explain the difference between ‘==’ and ‘is’ in Python.
A: ‘==’ checks for equality of values, while ‘is’ checks for equality of object identity. ‘is’ is used to check if two variables point to the same object in memory.

2. SQL:
Q: What is a primary key in a database?
A: A primary key is a unique identifier for each record in a table. It ensures that each record is uniquely identified and helps maintain data integrity.

Q: What is the difference between ‘WHERE’ and ‘HAVING’ in SQL?
A: ‘WHERE’ is used to filter rows based on a condition before grouping and aggregating data, while ‘HAVING’ is used to filter groups based on a condition after grouping and aggregating data.

3. Data Modeling:
Q: What is normalization in database design?
A: Normalization is the process of organizing data in a database to reduce redundancy and improve data integrity. It involves breaking down a large table into smaller tables and creating relationships between them.

Q: What is denormalization and when is it used?
A: Denormalization is the process of adding redundant data to a database to improve query performance. It is used when read operations are more frequent than write operations and when there is a need for faster data retrieval.

4. General:
Q: How would you handle missing values in a dataset?
A: Missing values can be handled by imputation (replacing missing values with a calculated value), deletion (removing rows or columns with missing values), or using algorithms that can handle missing data (such as decision trees or random forests).

Q: What is the difference between batch processing and real-time processing?
A: Batch processing involves processing data in large chunks at scheduled intervals, while real-time processing involves processing data as it arrives, providing instant results. Real-time processing is used for time-sensitive applications where immediate insights are required.

By familiarizing yourself with these questions and answers, you’ll be better prepared to tackle the technical aspects of a data engineering interview. Remember to practice coding exercises, review your SQL queries, and brush up on your data modeling skills. Good luck, and ace that interview!
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